A polynomial time algorithm for optimizing join queries
The dynamic programming algorithm for query optimization has exponential complexity. An alternative polynomial time algorithm, the IK-KBZ algorithm, is severely limited in the queries it can optimize. Other algorithms have been proposed, including the greedy algorithm, iterative improvement, and sim...
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Published in | Proceedings of IEEE 9th International Conference on Data Engineering pp. 345 - 354 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE Comput. Soc. Press
1993
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Subjects | |
Online Access | Get full text |
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Summary: | The dynamic programming algorithm for query optimization has exponential complexity. An alternative polynomial time algorithm, the IK-KBZ algorithm, is severely limited in the queries it can optimize. Other algorithms have been proposed, including the greedy algorithm, iterative improvement, and simulated annealing. The AB algorithm, which combines randomization and neighborhood search with the IK-KBZ algorithm, is presented. The AB algorithm is much more generally applicable than IK-KBZ, has polynomial time and space complexity, and produces near optimal plans in the space of outer linear join trees. On average, it does better than the other algorithms that do not do an exhaustive search like dynamic programming.< > |
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ISBN: | 0818635703 9780818635700 |
DOI: | 10.1109/ICDE.1993.344047 |